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ABSTRACT. Because of its high qualityand reliability, submerged arc welding(SAW) is one of the chief metal-joiningprocesses employed in industry for themanufacture of steel pipes used for vari-ous applications. This paper highlights astudy and analysis of various process-control variables and important weldbead quality parameters in SAW of pipes

manufactured out of structural steel (IS:2062). Mathematical models were devel-oped for the submerged arc welding of 6-mm-thick structural steel plates using3.15-mm-diameter steel electrodes.

The models were developed using thefive-level factorial technique to relate theimportant process-control variables welding voltage, wire feed rate, weldingspeed and nozzle-to-plate distance toa few important bead-quality parameters penetration, reinforcement, beadwidth, total volume of the weld bead anddilution. The models developed werechecked for their adequacy with the Ftest. Using the models, the main and in-teraction effects of the process-controlvariables on important bead geometryparameters were determined quantita-tively and presented graphically.

The developed models and the graphsshowing the direct and interaction effects

of process variables on the bead geome-try are very useful in selecting the processparameters to achieve the desired weld-bead quality. Also, the precision of the re-sults obtained with the mathematicalmodels were tested by using conformitytest runs. The test runs were conductednearly two years after the development ofmathematical models with the same ex-

perimental setup, and it was found theaccuracy of the predicted results is about98%. Further, these mathematical mod-els help to optimize SAW to make it amore cost-effective process.

Introduction

Submerged arc welding is one of themajor fabrication processes in industrybecause of its inherent advantages, in-cluding deep penetration and a smoothbead (Refs.1, 2). In the SAW of pipes, en-

gineers often face the problem of select-ing appropriate and optimum combina-tions of input process-control variablesfor achieving the required weld beadquality or predicting the weld bead qual-ity for the proposed process-control-vari-able values (Ref. 3). For automatic SAW,the control parameters must be fed to thesystem according to some mathematical

formula to achieve the desired results(Ref. 4). These important problems canbe solved with the development of math-ematical models through effective andstrategic planning, design and executionof experiments.

To achieve this, statistically designedexperiments based on the factorial tech-nique were used to reduce the cost andtime, as well as to obtain the required in-formation about the main and the inter-action effects on the response parameters(Refs. 5, 6). A cross section of a weldbead showing the important weld beadquality parameters is given in Fig. 1.

The mathematical models developedare useful for selecting correct processparameters to achieve the desired weldbead quality and to predict weld beadquality for the given process parameters(Ref. 7). These models facilitate opti-mization of the process and sensitivityanalysis. They also help to improve theunderstanding of the effect of process pa-rameters on bead quality, to evaluate theinteraction effects of bead parametersand to optimize the bead quality to ob-tain a high-quality welded joint at a rela-tively low cost with high productivity.

Prediction and Optimization of Weld Bead

Volume for the Submerged Arc Process Part 1

BY V. GUNARAJ AND N. MURUGAN

The main and interaction effects of the process-control variables on important beadgeometry parameters were determined quantitatively and are presented graphically

KEY WORDS

DilutionSAWOptimizationBead GeometryWeld Bead PenetrationWeld Bead ReinforcementWeld Bead WidthDesign Matrix

V. GUNARAJ is Assistant Professor of Me-chanical Engineering, Kumaraguru College ofTechnology, Coimbatore, Tamil Nadu, India.N. MURUGAN is Assistant Professor of Me-chanical Engineering, Coimbatore Institute ofTechnology, Coimbatore, Tamil Nadu, India.

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Experimental Procedure

The experiment was conducted at M/s.Sri Venkateswara Engineering Corp.,Coimbatore, India, with the followingsetup.

ADORE semiautomatic weldingequipment with a constant-voltage, rec-tifier-type power source with a 1200-Acapacity was used to join IS: 2062, struc-tural steel plates 300 x 150 x 6 mm. ESABSA1 (E8), 3.15-mm-diameter, copper-coated electrode in coil form and ESAB-brand, basic-fluoride-type (equivalent toDIN 8557) granular flux was used. Asquare butt joint with a 1-mm root open-

ing was selected to join the plates in theflat position, keeping the electrode posi-tive and perpendicular to the plate.

Plan of Investigation

The research work was carried out inthe following steps (Ref. 8).

Identifying the important process-control variables.

Finding the upper and lower limitsof the control variables.

Developing the design matrix. Conducting the experiments as per

the design matrix. Recording the responses. Developing the mathematical

models. Calculating the coefficients of the

polynomials. Checking the adequacy of the mod-

els developed. Arriving at the final mathematical

models. Conducting the conformity test. Presenting the direct and interaction

effects of different process parameters onbead geometry graphically.

Analyzing the results.

Identification of theProcess Variables

The independently controllableprocess parameters affecting bead geom-etry and the quality of the weld beadwere open-circuit voltage (OCV), wirefeed rate (F), welding speed (S) and noz-zle-to-plate distance (N). As it was notpossible to control the welding voltage(V) directly in the power source used forconducting the experiments, OCV wasused as a process variable. However, Vwas correlated to OCV through the de-velopment of a mathematical model.Using the developed model, welding

voltage (V) was calculated for all valuesof OCV and treated as a factor for draw-ing graphs and analyzing results.

Finding the Limits of the Process Variables

Trial runs were carried out by varyingone of the process parameters whilekeeping the rest of them at constant val-ues (Ref. 9). The working range was de-cided upon by inspecting the bead for asmooth appearance without any visibledefects such as surface porosity and un-dercut. The upper limit of a factor was

coded as +2 and the lower limit as 2.The coded values for intermediate valueswere calculated from the following rela-tionship: Xi = 2[2X - (Xmax + Xmin)] / (Xmax Xmin), where Xi is the required codedvalue of a variable X; X is any value of thevariable from Xmin to Xmax; Xmin is the lowerlevel of the variable and Xmax is the upperlevel of the variable. The process-variablelevels with their units and notations aregiven in Table 1.

Developing the Design Matrix

The selected design matrix, shown inTable 2, is a five-level, four-factor, cen-

tral composite rotatable factorial design(Ref. 10) consisting of 31 sets of codedconditions. It comprises a full replicationof 24 (=16) factorial design plus sevencenter points and eight star points. Allwelding variables at their intermediatelevel (0) constitute the center points, andthe combinations of each of the weldingvariables at either its lowest (2) or high-est (+2) with the other three variables attheir intermediate level constitute thestar points. Thus, the 31 experimentalruns allowed the estimation of the linear,quadratic and two-way interactive ef-

WELDING RESEARCH SUPPLEMENT | 287-s

R E S E A R C H / D E V E L O P M E N T / R E S E A R C H / D E V E L O P M E N T / R E S E A R C H / D E V E

L O P M E N T / R E S E A R C H / D E V

E L O P M E N T

Fig. 1 Cross section of a weld bead. Fig. 2 Direct effect of welding voltage (V) on bead parameters (P, R,

W, D).

Table 1 Process Control Parameters and Their Limits

Limits

Parameters Units Notation 2 1 0 +1 +2

Welding voltage volts V 24 26 28 30 32Wire feed rate m/min. F 0.70 0.93 1.16 1.39 1.62Welding speed m/min. S 0.43 0.51 0.59 0.67 0.75Nozzle-to-plate mm N 30.00 32.50 35.0 37.5 40.0distance

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fects of the welding variables on thebead geometry.

Conducting the Experiments as Per theDesign Matrix

The experiments were conducted asper the design matrix at random to avoidsystematic errors infiltrating the system.Beads were laid on the joint to join 6-mm-thick structural steel plates with theexperimental setup explained previously.

Recording the Responses

The welded plates were cut at the cen-ter of the bead to obtain 10-mm-wide testspecimens. These specimens were pre-pared by the usual metallurgical polish-ing methods and etched with 2% nital.The weld bead profiles were traced usinga reflective-type optical profile projectorwith 10X magnification. The bead di-mensions namely, penetration (P),width (W) and reinforcement (R) weremeasured with a digital planimeter with1-m accuracy. The areas of the baseplate melted and the excess metal de-posited over the base metal namely,area of penetration (AP) and area of rein-forcement (AR), respectively were alsomeasured using the planimeter. The per-

centage of dilution (D) and the total areaof the weld bead were calculated. Thetotal volume (T.V) of the weld bead, as-

suming the length of the bead (L) as unity,was also calculated. The observed andcalculated values are given in Table 2.

Development of Mathematical Models

The response function representingany of the weld bead dimensions can beexpressed as y = f (V, F, S, N). The rela-tionship selected, being a second-degreeresponse surface, is expressed as follows(Ref. 11):

Y = b0+ b1V + b2F + b3S + b4N + b11V2

+ b22F2+ b33S2+ b44N2+ b12VF + b13VS +b14VN + b23FS + b24FN + b34SN.

Evaluation of the Coefficients of Models

The values of the coefficients werecalculated by regression analysis with thehelp of the following equations (Ref. 12):

bn = 0.142857 Y 0.035714(XiiY)bi = 0.041667 (XiY)bii = 0.03125 (XiiY) 0.035714(XiiY) 0.035714 Ybij = 0.0625 (XijY)A computer program was developed

to calculate the value of these coeffi-

cients for different responses. The calcu-lated values are presented in Table 3.

Checking the Adequacy of theDeveloped Models

The adequacy of the models was thentested by the analysis-of-variance tech-nique (ANOVA) (Ref. 13). The calculatedvalue of the F ratio of the model developeddoes not exceed the tabulated value of Fratio for a desired level of confidence (se-lected as 95%). If the calculated value ofthe R ratio of the model developed ex-ceeds the standard tabulated value of theR ratio for a desired level of confidence(95%), then the models are adequate (Ref.14). From Table 4, it is evident that, for allthe models, the above conditions are sat-isfied and, hence, adequate.

Development of Final Mathematical Models

The final mathematical modelsdeveloped are given below. The process-control variables are in their coded form.

Penetration, mm = 3.57 0.113V + 0.33F 0.217S 0.001N + 0.048V2 + 0.1F2 +0.03S2 0.01N2 0.05VF + 0.06VS +0.04VN 0.01FS 0.01FN + 0.08SN

(1)

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Table 2 Design Matrix and Observed Values of Bead Parameters

Design Matrix Weld Bead Parameters

S. V F S N P R W AP AR D T.VNo. mm mm mm (mm2) (mm2) (%) (mm3)

1 1 1 1 1 3.52 1.70 10.15 20.7 24.48 42.40 48.82 +1 1 1 1 3.40 1.51 13.47 22.1 21.52 46.80 47.33 1 +1 1 1 4.75 2.32 11.05 24.5 22.80 47.50 51.54 +1 +1 1 1 4.10 1.85 15.64 26.3 24.15 50.30 52.25 1 1 +1 1 3.25 1.38 08.28 18.3 23.17 40.70 44.96 +1 1 +1 1 3.18 1.18 10.10 19.5 23.42 41.90 46.57 1 +1 +1 1 3.52 1.50 09.15 21.5 18.90 48.60 44.38 +1 +1 +1 1 3.33 1.82 09.86 23.2 19.25 49.80 46.69 1 1 1 +1 3.85 1.61 10.66 20.2 27.48 39.40 51.310 +1 1 1 +1 3.60 1.48 14.55 21.8 26.24 40.50 53.811 1 +1 1 +1 4.10 1.92 13.38 23.1 27.82 42.10 54.912 +1 +1 1 +1 3.80 1.80 15.96 26.5 31.16 42.90 61.813 1 1 +1 +1 3.20 1.37 08.70 17.7 24.52 38.60 45.514 +1 1 +1 +1 3.00 1.10 09.28 18.9 25.34 39.70 47.615 1 +1 +1 +1 4.10 1.75 09.01 20.3 25.55 40.80 49.816 +1 +1 +1 +1 3.88 1.50 10.00 21.1 23.87 42.30 49.117 2 0 0 0 4.10 1.62 10.28 19.4 24.25 41.10 47.218 +2 0 0 0 3.75 1.43 15.30 25.4 29.45 42.90 59.219 0 2 0 0 3.26 1.41 09.95 19.1 17.95 38.10 40.120 0 +2 0 0 4.97 1.75 10.96 27.7 21.53 51.00 54.321 0 0 2 0 4.25 2.30 16.11 25.3 31.33 41.30 61.2

22 0 0 +2 0 3.48 1.40 08.50 18.4 21.05 43.00 42.823 0 0 0 2 3.82 1.31 11.17 22.5 19.68 48.70 46.224 0 0 0 +2 3.58 1.27 12.05 23.2 27.83 42.50 54.625 0 0 0 0 3.45 1.15 11.20 20.9 21.80 47.10 44.426 0 0 0 0 3.47 1.30 10.58 21.7 21.40 46.50 46.627 0 0 0 0 3.66 1.27 09.92 21.9 19.80 48.20 45.428 0 0 0 0 3.60 1.31 11.13 21.2 19.90 47.60 44.529 0 0 0 0 3.30 1.16 10.56 20.5 21.10 45.70 44.930 0 0 0 0 3.60 1.27 10.84 22.6 21.50 47.30 47.831 0 0 0 0 3.92 1.45 11.05 22.1 24.60 48.50 47.6

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Reinforcement, mm = 1.27 0.08V +0.16F 0.18S 0.03N + 0.07V2+ 0.0782

+ 0.15S2 + 0.01N2 + 0.03VF + 0.03VS

0.014VN 0.003FS 0.02FN + 0.03SN(2)

Width of weld bead, mm = 10.76 +1.19V + 0.45F 1.9S + 0.23N + 0.41V2

0.17F2 + 0.29S2 + 0.12N2 0.04VF 0.64VS 0.15VN 0.35FS + 0.091FN 0.29SN (3)

Area of penetration, mm2 = 21.56 +1.05V + 1.85F 1.61S 0.212N +0.041V2 + 0.29F2 0.097S2 + 0.15N2 +0.14VF 0.21VS + 0.056VN 0.24FS 0.16FN 0.16SN (4)

Area of reinforcement, mm2 = 21.44 +0.44V + 0.187F 1.76S + 2.11N +1.39V2 0.39F2 + 1.22S2 + 0.62N2 +0.41VF 0.047VS + 0.14VN 0.94FS +

0.77FN 0.33SN (5)

Percentage of dilution = 47.27 + 0.74V +2.51F 0.25S 2.23N 1.31V2 0.71F2

1.31S2 0.44N2 0.09VF 0.3VS 0.31VN + 0.43FS 0.90FN + 0.17SN

(6)

Total weld bead volume, mm3 = 45.78 +1.58V + 2.2F 3.5S + 2.0N + 1.67V2 +0.17F2 + 1.34S2 + 0.97N2 + 0.28VF 0.21VS + 0.48VN 0.87FS + 0.64FN 0.77SN (7)

The significance of the coefficientswere also tested using the SYSTAT soft-ware package (Ref.15), and the reducedmodels with significant coefficients weredeveloped. It was found the reducedmodels were better than the full modelsbecause the reduced models have highervalues of R2 (adjusted) and lesser valuesof standard-error estimates than that of

the full models. The values of R2 andstandard error of estimates for both themodels are given in Table 5. The final re-

duced mathematical models with the sig-nificant coefficients are given below:Penetration, mm = 3.64 0.113V +0.33F 0.217S + 0.05V2 + 0.1F2 +0.03S2 (8)

Reinforcement, mm = 1.29 0.08V +0.16F 0.18S + 0.07V2 + 0.08F2 +0.15S2 (9)

Width of weld bead, mm = 10.87 +1.19V + 0.45F 1.9S + 0.23N + 0.4V2 0.19F2 + 0.28S2 0.64VS 0.35FS 0.29SN (10)

Area of penetration, mm2 = 21.64 +1.05V + 1.85F 1.6S + 0.29F2 (11)

Area of reinforcement, mm2 = 21.05 +




E L O P M E N T

Fig. 3 Effect of the welding performance factor on penetration. Fig. 4 Direct effect of welding voltage (V) on bead parameters (AP, AR and

T.V).

Table 3 Regression Coefficients of Models

Bead Parameters

SL. Coefficient P R W AP AR D T.VNo. mm mm mm (mm2) (mm2) (%) (mm3)

1 b0 3.572 1.27 10.76 21.56 21.44 47.27 45.782 b1 0.113 0.08 1.19 1.05 0.443 0.74 1.583 b2 0.33 0.16 0.45 1.85 0.187 2.50 2.204 b3 0.217 0.18 1.90 1.61 1.76 0.25 3.505 b4 0.001 0.03 0.23 0.21 2.11 2.23 2.006 b11 0.05 0.07 0.41 0.04 1.39 1.31 1.677 b22 0.10 0.08 0.17 0.29 0.39 0.71 0.178 b33 0.03 0.15 0.29 0.097 1.22 1.31 1.349 b44 0.01 0.01 0.12 0.15 0.62 0.44 0.9710 b12 0.05 0.02 0.05 0.14 0.41 0.09 0.2811 b13 0.06 0.03 0.64 0.21 0.047 0.28 0.2112 b14 0.038 0.014 0.15 0.056 0.14 0.31 0.4813 b23 0.011 0.003 0.35 0.24 0.94 0.43 0.8714 b24 0.01 0.02 0.09 0.16 0.77 0.90 0.6415 b34 0.083 0.03 0.29 0.16 0.33 0.17 0.77

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0.44V + 0.19F 1.76S + 2.11N + 1.43V2

+ 1.22S2 + 0.62N2 0.94FS + 0.77FN(12)

Percentage of dilution = 47.27 + 0.74V +2.51F 0.25S 2.25N 1.3V2 0.7F2 1.31S2 0.45N2 0.9FN (13)

Total weld bead volume, mm3 = 46.06 +1.58V + 2.2F 3.5S + 2.0N + 1.66V2 +1.35S2 0.95N2 0.87FS (14)

where V = welding voltage, F = wire feedrate, S = welding speed and N = nozzle-

to-plate distance.

Conducting the Conformity Tests

To determine the accuracy of themathematical models developed, con-formity test runs were conducted with thesame experimental setup. The confor-mity tests were conducted about twoyears after the mathematical modelswere developed. In the conformity testruns, the process variables were assignedsome intermediate values, and the re-sponses were measured. A comparison

was made between the actual and pre-

dicted values of bead parameters, and theresults are given in Table 6. The resultsshow the accuracy of the models devel-oped was above 97%.

Results and Discussions

The mathematical models furnishedabove can be used to predict the weldbead geometry by substituting the valuesof the respective process parameters.Also, the values of the control factors canbe obtained by substituting the value ofthe desired bead geometry. The responses

calculated from the reduced models foreach set of coded values of welding vari-ables are represented graphically in Figs.218; these show generally convincingtrends between cause and effect.

Direct Effects of Parameters

The Direct Effect of Welding Voltage (V) on

Bead Parameters

Figure 2 shows the penetration (P) andreinforcement (R) decrease marginallybut the bead width (W) and the percent-

age of dilution (D) increase steadily with

the increase in welding voltage (V). Theincrease in V results in increased arclength, which results in more melting atthe surface; hence, P decreases. Also, theincrease in the arc length results inspreading of the arc cone. Hence, W in-creases considerably as V increases. Asthe rate of decrease in P is less than Wsrate of increase with an increase in V, theweld pool size increases and, hence, Dincreases. The increased voltage resultedin increased bead width with corre-sponding reduction in reinforcement

height (R) due to the spreading of thebase of the arc cone. An excessive in-crease in voltage can result in nearly flatbead. Hence, R as well as the area of ex-cess metal deposited on the base platedecrease as V increases.

Jackson (Ref. 16) reported about therelationship between penetration andwelding voltage and current and weldingspeed using a welding technique perfor-mance factor, given as

where I = welding current (amps), S =

ISE

4

23


Fig. 5 Direct effect of wire feed rate (F) on bead parameters P, R, W

and D.

Fig. 6 Direct effect of wire feed rate (F) on bead parameters AP, AR

and T.V.

Table 4 Calculation of Variants for Testing the Adequacy of the Models

First order terms Second order terms Lack of fit Error-terms

Whether

Bead S.S D.F S.S D.F S.S D.F S.S D.F F-ratio R-ratio model isParameters adequate

Penetration 4.10 4 0.50 10 1.03 10 0.23 6 2.68 8.58 AdequateReinforcement 1.55 4 0.92 10 0.27 10 0.06 6 2.70 17.29 AdequateBead width 127.2 4 18.80 10 3.57 10 1.20 6 1.79 52.18 AdequateArea of Penetration 171.6 4 6.22 10 12.3 10 3.18 6 2.31 23.84 AdequateArea of 186.4 4 134.1 10 34.4 10 15.3 6 1.35 8.98 Adequate

reinforcementBead dilution 287.1 4 117.4 10 24.9 10 5.60 6 2.68 31.10 Adequate

Total weld bead 569.2 4 168.9 10 82.6 10 12.45 6 3.98 25.41 Adequatevolume

R-ratio =3.96 =(Sum of squares of first and second order terms/ Sum of D.F of first and second order terms)/M.S of error terms.F-ratio (10,6,0.05)=4.09 =M.S of Lack of fit/M.S of error terms.S.S =Sum of squares; D.F =Degree of freedom; M.S =Mean square =S.S/D.F.

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welding speed, (m/min [in. / min]) and E= welding voltage (in volts).

The welding technique performancefactor related to penetration, shown inFig. 3, is found to have the same trend asreported. In the figure, note P tends to in-crease with the increase of the weldingperformance factor.

Figure 4 shows the area of penetration(AP) increases but both area of reinforce-ment (AR) and total volume of weld bead(T.V) decrease to an optimum value as Vincreases from 24 to 28 volts; then ARand T.V increase for a further increase inV. As V increases, P decreases slightly,but W increases steadily, as shown in Fig.2. Weld pool size increases, resulting inan increase of AP. But R decreases grad-

ually as V increases from 24 to 28 volts,and, for further increase in the value of V,R is almost constant whereas W increasessteadily. Also, when V is increased from24 to 28 volts, the rates of decrease in Rand, thus, AR are more than the rate ofincrease in AP. Hence, T.V decreases asV is increased up to 28 volts and, with afurther increase in V, results in a steadyincrease in T.V.

The Direct Effect of Wire Feed Rate (F) on

Bead Parameters

Figures 5 and 6 show all the importantbead parameters P, R, W, D, AP, ARand T.V increase with the increase inF. This is because the arc current and,hence, the heat input increase with theincrease in F, and the wire melting anddeposition rate increase as F increases.Therefore, because of high heat input andmetal deposition rate, P, R, W, D, AP, ARand T.V all increase when F increases.

The Direct Effect of Welding Speed (S) on

Bead Parameters

From Figs. 7 and 8, it is apparent the

welding speed (S) has a negative effect onall the bead parameters. This is because,

when S increases, the welding torch trav-els at a greater speed over the base metal,resulting in a lower metal deposition rateon the joint. Also, the heat input de-creases appreciably when S increases.Hence, because of less heat input and alower metal deposition rate, P, R, W, D,AP, AR and T.V all decrease with the in-crease in the value of S.

The Direct Effect of Nozzle-to-Plate

Distance (N) on Bead Parameters

Figure 9 shows that as the nozzle-to-

plate distance (N) increases, R and D de-crease, but the reverse is true with W.These effects occur because the arc cur-rent and, hence, the heat input decreasewith the increase in N. Because of the re-duced heat input, the value of R and Ddecrease when N increases. As N in-creases, the arc length increases. This in-crease in the arc length spreads the arccone at its base. Also, the metal fusionrate increases slightly at higher values ofN because of the joules heating effect.Therefore, the value of W increases as Nincreases. P is not significantly affected

by N.

Figure 10 shows AP decreases slightlybut AR and T.V increase steadily with the

increase in N. As N increases, P de-creases very little and, hence, AP de-creases. The decrease in R (from 1.31 to1.27 mm ) is much lower compared tothe increase in W (from 11 to 12 mm)when N is increased, as shown in Fig. 9.Hence, AR increases appreciably withthe increase in N. Also, the increase inAR is steady compared to the decrease inAP as N increases. Therefore, the totalarea and T.V of the weld bead increasesteadily with the increase in N.

Interaction Effects of Process Variables

Interaction Effects of Wire Feed Rate (F) and

Welding Speed (S) on Bead Width (W)

Figure 11 shows the interaction effectof F and S on W. From the direct effectsof F and S (shown in Figs. 5 and 6) on W,it was found F has a positive effect but Shas a negative effect on W. Because ofthese effects, the value of W increaseswith the increase in F for all values of S.But, because of the negative effect of S onW, the rate of increase W with the in-crease in F gradually decreases as S in-

creases from its lower limit to upper limit.




E L O P M E N T

Fig. 7 Direct effect of welding speed (S) on bead parameters P, R, W

and D.Fig. 8 Direct effect of welding speed (S) on bead parameters AP, AR

and T.V.

Table 5 Comparison of Squared Multiple R Values and Standard Error of Estimate Values forFull and Reduced Mathematical Models

Standard errorR2 Value (adjusted) of estimate

S. Bead Full Reduced Full ReducedNo. Parameters models models models models

1 Penetration 0.598 0.700 0.280 0.2422 Reinforcement 0.777 0.819 0.144 0.1303 Bead width 0.941 0.943 0.546 0.5334 Area of penetration 0.850 0.878 0.984 0.8875 Area of reinforcement 0.748 0.774 1.762 1.6716 Percent dilution 0.869 0.880 1.379 1.3177 Total weld bead volume 0.786 0.808 2.437 2.312

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Fig. 9 Direct effect of nozzle-to-plate distance (N) on bead para-

meters P, R, W and D.Fig. 10 Direct effect of nozzle-to-plate distance (N) on bead para-

meters AP, AR and T.V.

Fig. 11 Interaction effect of F and S on bead width. Fig. 12 Interaction effect of F and S on bead width (response sur-

face).

Fig. 13 Interaction effect of V and S on bead width. Fig. 14 Interaction effect of V and S on bead width (response sur-

face).

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Figure 12 shows the response surfaceand the contour plot of W for the inter-action of F and S when V and N are keptat zero (0). From this contour surface, itis found W is lowest (8 mm) when F is atits minimum value with S at its maxi-mum value; W is highest (17 mm) whenF is at its maximum value with S at itsminimum value.

Interaction Effect of Welding Voltage (V) and

Welding Speed (S) on Bead Width (W)

From Fig. 13, it is evident W increasesas V increases for all values of S. But thisincreasing trend of W with the increasein V decreases gradually as S increases.These effects occur because V has a pos-itive effect but S has negative effect on W,as shown in Figs. 2 and 7. At the lowestvalue of V, W is maximum (11 mm) forthe lower value of S (0.43), and W is min-imum (8 mm) for the higher value of S(0.75). Also, when V is at its maximumvalue, W is maximum (24 mm) for the

lower value of S and is minimum (11 mm)

for the higher value of S. These effects arefurther explained in Fig. 14, which showsthe contour plot of W for the interactioneffect of V and S when F and N are at theirmidpoints (0). From the contour surfaceof W, it is observed W is maximum (about20 mm) when V is at its upper level (+2)with S at its lower level (2); W is mini-mum (about 9 mm) when V is at its lowerlevel (2) with S at its upper level (+2).

Interaction Effect of Wire Feed Rate (F) andNozzle-to-Plate Distance (N) on Bead

Dilution (D)

Figure 15 shows the interaction effectof F and N on D. From the direct effectsof F and N on D (as discussed previouslyand shown in Figs. 5 and 9), it was foundF has a positive effect but N has a nega-tive effect on D. Because of these effects,and their interaction effect on D shownin Fig. 15, the value of D increasessteadily with the increase in F for all val-ues of N. But this rate of increase in D

with increase in F gradually decreases as

N increases from 30 to 40 mm.Figure 16 shows the response surface

of D for the interaction effect of F and N.The contour surface shows D is maxi-mum (54.6%) when F is at its maximumlimit (+2) with S at its minimum limit (2),and D is minimum (36.4%) when F is atits lower level (2) with N at its upperlevel (+2).

Interaction Effect of Wire Feed Rate (F) and

Welding Speed (S) on Total Weld BeadVolume (T.V)

Figure 17 shows T.V increases steadilywith the increase in F for any given valueof S. But this increase of T.V with the in-crease in F decreases gradually as S in-creases from its lower value (0.43) to itsupper value (0.75). These effects aremainly due to the positive effect of F butnegative effect of S on T.V (as explainedpreviously and shown in Figs. 6 and 8).

Figure18 shows the response surfaceof T.V due to the interaction effects of F

and S. The contour graph also shows the




E L O P M E N T

Fig. 15 Interaction effect of F and N on bead dilution.Fig. 16 Interaction effect of F and N on bead dilution (response sur-

face).

Fig. 17 Interaction effect of F and S on total weld bead volume. Fig. 18 Interaction effect of F and S on total weld bead volume (re-sponse surface).

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same trend for T.V. This graph shows T.Vis maximum (64.2 mm3) when F is at itsmaximum value with S at its minimumlimit. T.V is minimum (42.5 mm3) when Fis at its lower value with S at its upperlimit.

Conclusions

The following conclusions were

drawn from the above investigation:1) The five-level factorial technique

can be employed easily for developingmathematical models for predicting weldbead geometry within the workable re-gion of process parameters for SAW ofpipes.

2) The models developed can be em-ployed easily in the form of a program forautomatic and robotic welding for ob-taining the desired high-quality welds.

3) The welding process variable wirefeed rate has a positive effect, but weld-ing speed has a negative effect on all the

bead parameters.4) Penetration reduces as welding

voltage increases, but bead width and di-lution increase considerably with the in-crease in voltage.

5) Reinforcement is least when all theprocess variables are at their upper limit(+2) and F is at its lower limit.

6) Nozzle-to-plate distance has a neg-

ative effect on all the bead parameters ex-cept bead width and total volume of theweld bead.

7) Most of the direct and interactioneffects of the process variables on thebead parameters show generally con-vincing trends between cause and effect.

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